Posts Tagged ‘Drop Ship’

In a recent research note and a corresponding press release, Gartner’s Andrew Kyte assessed the current level of world-wide IT Debt [1] at about $500 billion. Andrew actually considers $500 billion a conservative estimate, expecting it to grow to $1 trillion by 2015. As was pointed out by David Nagel, $1 trillion is more than four times total worldwide enterprise software expenditures this year.

I am publishing two posts in order to put these staggering figures in perspective. This post primarily addresses the business design ramifications of the numbers quoted above. A follow-on post in the coming week will explore the dire repercussions of disregarding the proven practice “an ounce of prevention is worth a pound of cure.” It will also offer an explanation rooted in our business context why this tried and true wisdom has so often been disregarded over the past decade.

The first thing to point out about the Kyte/Gartner figures is that these figures are the cost of fixing, not the value that could be lost due to the myriad malfunctions that a $1 trillion worth of software quality deficits can cause. It is like the loss incurred through fixing the truck in Figure 1 below. The cost of fixing might be $10,000. The corresponding loss of value due to the time it took to carry out the fixing of the truck is vividly captured in the quip written on the back of the sleeper: “Day late $100,000 short.”

If you accept this premise, one real risk of a high level of IT debt is the deterioration of services provided through the software. An even bigger risk, however, is obsolescence of business designs due to the software systems decaying to the point that adding critical services is next to impossible. For example, consider the following B2B eCommerce services for retailers (taken from an unrelated exchange I recently had with my friend Erik Huddleston):

Vendor drop ship

Catalog/data sync

Vendor management

Compliance

It is unlikely a 10-year-old eCommerce software system whose upkeep was neglected for the past decade would have enough changeability left in it to enable providing such services. Lacking these services, the business is likely to revert to outdated designs for generating and recapturing value.

The B2B eCommerce situation discussed above is not really different from the classical dynamics of regression in the development of a child. It is, of course, poignant when a child suffers during one phase or another in his/her development. The bigger poignancy, however, is that the struggling child gets stuck. He/she is unable to move on to the next developmental phase(s). Other children surpass him/her.

What it means in less metaphorical terms is that an incumbent with a significant IT debt might fall behind new entrants who are not (yet?) saddled with such debt. The new entrants can utilize the flexibility of their software to satisfy customer needs in ways that the incumbent’s legacy software will be hard pressed to meet. Moreover, the new entrants can modify their software in response to actual customer feedback in a much faster manner than the ‘neglectful incumbent’ can.

As an incumbent, you need to really start worrying about your IT debt if you accept the inevitability of the transformation driven by the confluence of Cloud, Mobile and Social (see Consumerization of Enterprise Software). No matter what industry you are in, the versatility, modularity, flexibility and mobility of the forthcoming consumerized enterprise software apply to every aspect of your business design. The IT debt you did not ‘pay back’ stands in the way of modernizing your business design.

Footnotes:

[1] Kyte/Gartner define IT Debt as “the costs for bringing all the elements [i.e. business applications] in the [IT] portfolio up to a reasonable standard of engineering integrity, or replace them.” In essence, IT Debt differs from the definition of Technical Debt used in The Agile Executive in that it accounts for the possible costs associated with replacing an application. For example, the technical debt calculated through doing code analysis on a certain application might amount to $500K. In contrast, the cost of replacement might be $250K, $1M or some other figure that is not necessarily related to intrinsic quality defects in the current code base.